| ObjectiveAnkylosing spondylitis(AS)is a form of spondyloarthritis.Despite the progress of the diagnosis and treatment technology and targeting drugs in recent years,improve the early diagnosis,long-term prognosis and the degree,but it is still early missed diagnosis was higher,easily with joint damage,with huge individual differences.Even if the result of the treatment,spinal injury is still occurence.Bone bridge formation is the most serious prognostic outcome of AS.Current mechanism research of AS is insufficient to explain the process of bone bridge formation,and effective biomarkers and prediction methods are also lacking.RNA sequencing(RNA-seq)is a popular method to explore the pathogenesis at the gene level and reliable biomarkers with clinical significance.In recent years,evidence has continuously confirmed that lncRNA plays a key role in various AS processes,such AS inflammatory dependent pathways,osteogenesis,adipogenesis,angiogenesis,Notch signaling pathway,TNF signaling pathway,etc.In this study,through analysis of differentially expressed RNA profile between AS patients and healthy control group,found new lncRNAs in AS,and expore their possible ceRNA mechanism.Then quantitative real-time polymerase chain reaction(q RT-PCR)was used to detect the expression of target lncRNAs in AS patients and normal population.Furthermore,explore the relationship between the expression level of target lncRNAs and the clinical characteristics and prognostic prediction.And analyze the prognostic value of potential lncRNA biomarkers in AS.Methods1.Screening target lncRNAs:lncRNA expression profile and m RNA expression profile in whole blood cells of 5 AS patients and 3 healthy controls were obtained by RNA-seq.Then verified and annotated the quality of RNA.RNA expression profile was analyzed using R language,and RNA with significantly different expression was identified.The criteria for significantly different expression were defined as fold change(FC)?2 or?0.5,false discovery rate(FDR)<0.05.GO analysis and KEGG pathway analysis were performed on the differentially expressed RNA profile,and the GO items and KRGG pathway with P<0.05 were considered to be significantly enriched.Differentially expressed lncRNAs(DElncRNAs)with consistent and significantly different expression in patients or with GO and KEGG enriched in osteogenic items were selected as candidate lncRNAs.Dozens of known biomarkers of AS were obtained through Gene Cards and literature retrieval,and the correlation between candidate lncRNAs and known biomarkers of AS was observed by R language multi-gene correlation analysis,and valuable lncRNAs were screened AS targets.2.m RNA expression profile enrichment analysis and miRNA prediction:GO and KEGG enrichment analysis was performed on m RNAs expression profile and co-expressed m RNAs by the two target lncRNAs.Co-expressed genes are the upstream and downstream encoding genes of lncRNA,and may share a common regulatory mechanism with lncRNA.Co-expression analysis was performed by calculating Pearson correlation coefficient between target differentially expressed lncRNAs and genes encoded in the range of 10kb.The correlation coefficient between the target lncRNAs and the coding gene pairs should be>0.6 and P<0.05.The two data sets were combined to obtain the cis-action target of lncRNAs.Subsequently,GO analysis and KEGG pathway analysis were performed on all m RNA gene profiles,and GO term or KRGG pathway with P<0.05 were considered to be significantly enriched.m RNA significantly enriched in osteogenesis related items or AS pathogenesis related items were searched.Diana-mirpath V2.0,an online miRNA database,was used to analyze the interaction between lncRNAs and miRNAs,and the miRNAs correlated with candidate lncRNAs were obtained.The interaction between m RNA and miRNA was analyzed using the mir NA-mrna specialist prediction website Target Scan.3.Construction of ceRNA network:the intersection of acquired lncRNA-miRNA and miRNA-m RNA data was obtained to selected miRNAs correlated with both target lncRNA and m RNA.Based on those key RNAs,the key lncRNA-miRNA-m RNA ceRNA network of AS was established,and Cytoscape software was used to realize data visualization.4.q RT-PCR:68 AS patients(38 without bone bridge formation and 30 with bone bridge formation)and 29 healthy persons were collected for peripheral blood samples and clinical indicators.Using Trizol method to extract total RNA from peripheral blood mononuclear cells,and spectrophotometer was used to test the absorbance of samples at A260/A280.q RT-PCR was used to detect the expression level of target lncRNAs in AS patients and healthy control.Each sample was repeated three times,and relative quantity(RQ)was calculated,RQ=2-??CT.5.Collection of clinical data and indicators:General clinical data,such as age,course of disease,delayed diagnosis,ESR,C-reactive protein,etc,were collected.Ankylosing spondylitis disease activity scores based on CRP were calculated(ASDAScrp).Bath Ankylosing Spondylitis Disease Activity Index(BASDAI),Visual analogue Scale of low back pain,VAS)Modified Stoke Ankylosing Spondylitis Spine Score,MSASSS,Spondyloarthritis Research Consortium of Canada(SPARCC),etc.6.Explore the clinical value and data analysis methods of target lncRNAs:SPSS 24.0software was used for analysis.1)The measurement data conforming to normal distribution were expressed as X±S,t test was used for comparison between the two groups(T'test was used for uneven variance),and ANOVA was used for comparison between the three groups.Median(M)/(P25-P75)was used for measurement data with non-normal distribution,and non-parametric test was used for comparison between groups.Statistical data were expressed in percentage and number of cases,and comparison between groups was performed by?~2 test,Fisher test or binomial distribution test.2)The expression differences of target lncRNAs were observed in different disease activities and structural damage degrees.3)Correlation analysis,the correlation between measurement data consistent with normal distribution,observation according to Pearson correlation coefficient;The observation index was Spearman rank correlation coefficient.4)Linear regression model was used to analyze the influencing factors of measurement data.Single factor and multiple factor logistic regression models were used to analyze the influencing factors of counting data,including single factor and multiple factor Logistic regression.5)The area under the calibration curve and ROC curve was used to evaluate the prediction performance,specificity and sensitivity of the target lncRNA and model.Results1.RNA sequencing results:A total of 205 DElncRNAs were obtained,of which 67were up-regulated and 138 were down-regulated.218 DEm RNA,including 153up-regulated m RNA and 65 down-regulated m RNA.2.Obtain target lncRNAs:Combined with enrichment analysis,lncRNA ENSG00000254910,lncRNA ENSG00000278238 and lncRAN ENSG00000235245with high expression level,good consistency and unannotated function were selected as candidate lncRNAs.Further analysis showed that lncRNA ENSG00000254910 and lncRNA ENSG00000278238 were associated with more than 10 known biomarkers of AS,including structural damage markers.It was suggested that lncRNA ENSG00000254910 and lncRNA ENSG00000278238 were closely related to AS,so they were the target lncRNAs of this study.3.Enrichment analysis of m RNA expression profile:Enrichment analysis of m RNA expression profile showed that the co-expression m RNA of 5 lncRNA ENSG00000254910 and lncRNA ENSG00000278238(SOCS3,TNFAIP3,EDN1,ATF4,JUN was significantly enriched in TNF signaling pathway,which ranked first in KEGG analysis.4.miRNA prediction and ceRNA network:In the exploration of miRNAs,lncRNA ENSG00000254910 and lncRNA ENSG00000278238 matched 57 interacting miRNAs,SOCS3,TNFAIP3,EDN1,ATF4 and JUN obtained 964 interacting miRNAs.The intersection of the two was calculated and 30 key miRNAs were obtained.The constructed lncRNA-miRNA-m RNA ceRNA network suggested that it might play a role in AS through TNF signaling pathway.5.Expression of lncRNA ENSG00000254910 and lncRNA ENSG00000278238 in AS and healthy control:Expression of the two target lncRNAs in AS patients with and without bone bridge formation was significantly higher than that in healthy control(P<0.01).The expression level of lncRNA ENSG00000254910 in the group with bone bridge formation was higher than that in the group without bone bridge formation(P=0.005),and the expression level in patients was significantly higher than that in the healthy population(P<0.001).The expression of lncRNA ENSG00000278238 in the group with bone bridge formation was similar to that in the group without bone bridge formation(P=0.057),but also significantly higher than healthy control(P=0.001).6.Expression of target lncRNAs on different disease activity states:lncRNA ENSG00000254910 expression was statistically different among the four ASDAScrp disease activity groups(P=0.008),and the expression of lncRNA ENSG00000254910in the BASDAI remission group was higher than the activity group(P=0.018).Lnc RNA ENSG00000278238 showed no significant difference in disease status among all groups.7.Expression of target lncRNAs on different structural damage states:The expression of lncRNA ENSG00000254910 was gradually increased in patients with grade II,III and IV Sacroiliac joint(P=0.006),and was significantly higher in patients with X-ray spinal involvement(P=0.002)and bone bridge formation(P=0.005)than in patients without involvement.Lnc RNA ENSG00000278238 was increased in AS patients with bone marrow edema on sacroiliac joint MRI(P=0.046).8.Correlation analysis:lncRNA ENSG00000254910 was correlated with VAS score(r=0.371,P=0.005),BASDAI(r=0.368,P=0.002),and structural damage index:Occipital wall distance(r=0.217,P=0.027),sacroiliac joint X-ray grade(r=0.381,P=0.004),BASFI score(r=0.270,P=0.026)and bone bridge formation(r=0.380,P=0.003)were correlated.Lnc RNA ENSG00000278238 was correlated with BASDAI(r=0.325,P=0.007)and Sacroiliac joint X-ray grade(r=0.272,P=0.041).9.Regression analysis:The relative expression level of target lncRNAs and clinically relevant indicators were taken as independent variables and brought into the linear regression model with ASDAScrp as dependent variables.Eventually lncRNA ENSG00000254910(?=-0.229,t=3.080,P=0.003),ESR(?=0.465,t=4.366,P<0.001),CRP(?=0.391,t=3.681,P=0.001)were included in the model(P<0.001).The model R~2value was 0.680,F value was 42.016,and P value was<0.001.Linear regression analysis of m SASSS score as dependent variables showed that lncRNA ENSG00000254910(?=0.473,t=3.560,P=0.001)and ASDAScrp(?=0.287,t=2.157,P=0.037)were included in the model.The total R~2 value of the model was 0.252,F value was 7.430,and P value was 0.002.Logistic regression analysis of bone bridge formation as dependent variable suggested that lncRNA ENSG00000254910(OR=1.324,P=0.048),delayed diagnosis time(OR=1.289,P=0.035),X-ray grade of sacroiliac joint(OR=4.613,P=0.026)is a clinical risk factor for bone bridge formation,especially lncRNA ENSG00000254910.The area under ROC curve for predicting bone bridge formation was 0.739,Jordan index was 0.405,sensitivity was 0.800,and specificity was 0.605.10.Prediction model for bone bridge formation:The model was based on logistic analysis results,including indicators lncRNA ENSG00000254910,delayed diagnosis time,and X-ray grade of sacroiliac joint.The calibration curve showed that the predicted probability of the model was very close to the actual probability.The area under the ROC curve of the model was 0.870(95%CI=0.780-0.959,P<0.001),and the optimal Yorden index was 0.637(sensitivity=0.900,specificity=0.737).Conclusion1.RNA expression profiles in whole blood cells of AS patients and healthy controls were obtained for sequencing.RNA differential expression profiles,coexpression gene analysis,GO and KEGG pathway analysis were performed.It was found that lncRNA ENSG00000254910 and lncRNA ENSG00000278238 had good consistency of expression in AS patients and their functions had not been annotated.Compared with healthy people,their expressions were significantly different and were related to multiple biomarkers of AS.2.The ceRNA network constructed by lncRNA-miRNA-m RNA intersection combination suggested that lncRNA ENSG00000254910 and lncRNA ENSG00000278238 might regulate TNF signaling pathway through the mechanism of ceRNA network and participate in the development or progression of AS.3.Lnc RNA ENSG00000254910 is associated with various disease activity indicators and structural damage indicators,and is one of the risk factors for bone bridge formation,and may be an effective predictor of bone bridge formation in AS patients.4.The model based on lncRNA ENSG00000254910 and traditional clinical risk factors(delayed diagnosis time and X-ray stage)can predict the occurrence of bone bridge formation in AS patients,providing a new idea for the individualized diagnosis and treatment of AS. |
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